I would like to use ClearML together with Hydra multirun sweeps, but I’m having some difficulties with the configuration of tasks.

Based on a hydra configuration file similar to this:
` # @package global

defaults:

• override /hydra/launcher: clearml
• override /model: my_awesome_model
• self

trainer:
max_epochs: 500

hydra:
mode: MULTIRUN
sweeper:
params:
model.width: 256,1024
model.depth: 1,3
model.dropout: 0.0,0.5 `What I want to achieve, is that each of the (N=8, in this example) sub-runs here will be enqueued on ClearML for remote execution. Notice that I have made my own “ClearML” hydra launcher to achieve this, which is quite similar to https://hydra.cc/docs/plugins/joblib_launcher/ in implementation.

Such a launcher gets access to a config loader, the global config object as well as a list of overrides (for each sub-task). So what I have done is essentially something like this:
` def _launch_job(
self,
overrides: Sequence[str],
requirements_file: Path,
idx: int,
) -> JobReturn:
"""Launch a ClearML task for the specified Hydra overrides."""

    # Create a ClearML task with specified script and requirements.
    task: Task = Task.create(
        project_name=self.config.clearml.task_name,
        task_name=self.config.clearml.task_name,
        script=self.task_function.__code__.co_filename,
        requirements_file=requirements_file.as_posix(),
        add_task_init_call=False,
    )

    # Connect the configuration object to the task.
    # This enforces that the overall configuration
    # is automatically bound when the task is launched.
    sweep_config = self.hydra_context.config_loader.load_sweep_config(
        self.config, list(overrides)
    )
    configuration: dict = OmegaConf.to_container(sweep_config)  # type: ignore
    configuration.pop("hydra", None)  # Hydra config should be removed
    task.set_configuration_object(
        name="OmegaConf",
        description="OmegaConf auto-generated from hydra multirun sweeper",
        config_text=OmegaConf.to_yaml(configuration, resolve=False),
        config_type="OmegaConf YAML",
    )

    # Connect the Hydra overrides to the task.
    args = {"_allow_omegaconf_edit_": False}
    task.connect(args, "Hydra")

    # Schedule the task to run on the specified queue.
    Task.enqueue(task, queue_name=self.queue)
    log.info(f"Launched ClearML task {task.id} on queue {self.queue}.")

    # Register a user property to track the Hydra job index.
    task.set_user_properties(idx=idx)
    task.add_tags(self.sweep_id) `However, now I am struck with errors due to how ClearML binds with Hydra.  It appears to me, that the underlying Hydra-binding from ClearML receives the  ` OmegaConf `  on the task, and tries to merge this onto the default configuration object of the hydra execution. However, in my example, I can have module overrides on the model, e.g., where the configured model exposes a different parameter-set than the default model, etc., that results in the merge failing.

Am I doing something wrong? Is there a way to configure the hydra binding to naively enforce the OmegaConf from the task?